报告题目：Locally Adaptive Rank-Constrained Optimal Tone Mapping（山东大学博士高端论坛）
报告人：XIAOLIN WU, McMaster University, Canada
时间：6月29日 10：00
地点：山东大学青岛校区信息学院N5楼4楼会议室
报告人简介：
Prof. Wu got his B.Sc. from Wuhan University, China in 1982, and Ph.D. from University of Calgary, Canada in 1988, both in computer science. Dr. Wu started his academic career in 1988, and has since been on the faculty of University of Western Ontario, New York Polytechnic University (NYU-Poly), and currently McMaster University, where he is a professor at the Department of Electrical & Computer Engineering. Dr. Wu is an IEEE fellow and holds an NSERC senior industrial research chair. His research interests include image processing, data compression, digital multimedia, low-level vision, and network-aware visual communication. He has published over 350 research papers and holds four patents in these fields, and served as associated editors of IEEE Transactions on Image Processing and of IEEE Transactions on Multimedia. He also served on technical committees of many IEEE international conferences/workshops on image processing, multimedia, data compression, and information theory. Dr. Wu received numerous international awards and honors, including Velux Fellowship, Nokia Research Fellowship, Monsteds Fellowship, McMaster Distinguished Engineering Professorship, UWO Distinguished Research Professorship, and the 2008 VCIP best paper award.
武教授于1982从中国武汉大学获得学士学位，1988在加拿大卡尔加里大学获得博士学位，此后在西安大略大学、纽约理工大学（NYY-PYL）等高校担任教职，现任麦克马斯特大学电气与计算机工程系教授。武教授是IEEE会士，并担任NSERC高级客座教授。他的研究兴趣包括图像处理、数据压缩、数字多媒体和计算机视觉。他发表了350多篇研究论文，拥有四项国际专利，并担任IEEE图像处理和多媒体等IEEE会刊的副主编。他还加入了多个IEEE国际会议/技术研讨会的图像处理、多媒体、数据压缩和信息理论等方面的技术委员会。武教授获得了多项国际奖项和荣誉，包括维洛克斯奖学金、诺基亚研究奖学金、Munists奖学金、McMaster杰出工程教授、杰出研究教授和2008届VCIP最佳论文奖。
报告摘要：
High dynamic range (HDR) tone mapping is formulated as an optimization problem of maximizing perceivable spatial details given the limited dynamic range of display devices. This objective can be attained, as supported by our results, by a novel image display methodology called locally adaptive rank-constrained optimal tone mapping (LARCOTM). The scientific basis for LARCOTM is that the maximum discrimination power of human vision system can only be achieved in a relatively small locality of an image. LARCOTM is fundamentally different from existing HDR tone mapping techniques in that the former can preserve pixel value order statistics within localities in which human foveal vision retains maximum sensitivity, while the latter cannot. As a result, images enhanced by LARCOTM are free of artifacts such as halos and double edges that plague other HDR methods.
